Transfer Learning Models in Medical Image Anomaly Detection

Jayabharathi S and V.Ilango

International Journal of Scientific Research in Science and Technology, 2025, vol. 12, issue 2, 1186-1189

Abstract: Transfer learning is a common method for moving information from one field to another. In medical imaging applications, transfer from ImageNet has emerged as the de-facto method, in spite of variations in the requirements and picture properties among the domains. The elements that define the usefulness of transfer learning to the medical field are unknown, nevertheless. Recently, the long-held belief that features from the source domain are reused has come under scrutiny.

Keywords: Transfer Learning; Models In Medical; Medical Image Anomaly; Image Anomaly Detection; Learning Models (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:etm:ijsrst:v12:y2025:i2:id:774

DOI: 10.32628/IJSRST251222678

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